ME 3227 Design of Machine Elements (Spring 2021, Spring 2022, Fall 2022, Spring 2023)
In this course, the material is presented in the context of the overall design process, but emphasizes the quantitative methods used to size machine elements. Machine design covers a wide range of topics, and a subset of the needed materials is selected based on the combination of:
- General ideas about how each part of knowledge integrates into the machine design.
- Analytical, semi-analytical, and empirical methods that are most likely to be encountered.
- A variety of topics in the machine element design.
ME 3295 Computational Foundations of Digital Manufacturing (Fall 2021)
The purpose of this course is to introduce students to the multiple components that integrate to create future manufacturing. This introductory class will explore modern data science and AI (e.g., Bayesian Learning and Inference, Deep Neural Network, and Reinforcement Learning) and will aim to quickly learn data visualization, integrate various sensors with machines, perform process monitoring and control, take test measurements using machine visions, explore the process of discovering causality structure, and finally introduce cloud computing and digital security and privacy to control multiple machines.
ENGR 3215 Statistical Quality Control and Reliability for Manufacturing (Fall 2023)
This course aims to provide a comprehensive understanding of the foundations of quality control and reliability in manufacturing systems. By the end of semester, students will be able to apply principles and methods of modern quality control to measure and analyze both attribute and measurement data. They will also gain knowledge in developing and utilizing control charts, conducting manufacturing process capability studies, analyzing measurement data through ANOVA and linear regression, designing experiments, implementing Taguchi methodology and response surface techniques, and predicting and modeling reliability in manufacturing systems. Additionally, students will gain expertise in acceptance sampling techniques to ensure consistent quality control in manufacturing.